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At least 181 records · Page 10
All sourcesNASA NTRSDOE OSTI
NASA NTRS2017

Quantifying Pilot Contribution to Flight Safety During an In-Flight Airspeed Failure

Accident statistics cite the flight crew as a causal factor in over 60% of large transport fatal accidents. Yet a well-trained and well-qualified crew is acknowledged as the critical center point of aircraft systems safety and an integral component of the entire commercial aviation system. A human-in-the-loop test was conducted using a Level D certified Boeing 737-800 simulator to evaluate the pilot's contribution to safety-of-flight during routine air carrier flight operations and in response to system failures. To quantify the human's contribution, crew complement was used as an independent variable in a between-subjects design. This paper details the crew's actions and responses while dealing with an in-flight airspeed failure. Accident statistics often cite flight crew error (Baker, 2001) as the primary contributor in accidents and incidents in transport category aircraft. However, the Air Line Pilots Association (2011) suggests "a well-trained and well-qualified pilot is acknowledged as the critical center point of the aircraft systems safety and an integral safety component of the entire commercial aviation system." This is generally acknowledged but cannot be verified because little or no quantitative data exists on how or how many accidents/incidents are averted by crew actions. Anecdotal evidence suggest crews handle failures on a daily basis and Aviation Safety Action Program data generally supports this assertion, even if the data is not released to the public. However without hard evidence, the contribution and means by which pilots achieve safety of flight is difficult to define. Thus, ways to improve the human ability to contribute or overcome deficiencies are ill-defined.

Etherington, Timothy J.↗
NASA NTRS1976

Best-range flight conditions for cruise-climb flight of a jet aircraft

The Breguet range equation was developed for cruise climb flight of a jet aircraft to include the climb angle and is then maximized with respect to the no wind true airspeed. The expression for the best range airspeed is a function of the specific fuel consumption and minimum drag airspeed and indicates that an operational airspeed equal to the fourth root of three times the minimum-drag airspeed introduces range penalties of the order of one percent.

Hale, F. J.↗
NASA NTRS1993

A robust rotorcraft flight control system design methodology utilizing quantitative feedback theory

Rotorcraft flight control systems present design challenges which often exceed those associated with fixed-wing aircraft. First, large variations in the response characteristics of the rotorcraft result from the wide range of airspeeds of typical operation (hover to over 100 kts). Second, the assumption of vehicle rigidity often employed in the design of fixed-wing flight control systems is rarely justified in rotorcraft where rotor degrees of freedom can have a significant impact on the system performance and stability. This research was intended to develop a methodology for the design of robust rotorcraft flight control systems. Quantitative Feedback Theory (QFT) was chosen as the basis for the investigation. Quantitative Feedback Theory is a technique which accounts for variability in the dynamic response of the controlled element in the design robust control systems. It was developed to address a Multiple-Input Single-Output (MISO) design problem, and utilizes two degrees of freedom to satisfy the design criteria. Two techniques were examined for extending the QFT MISO technique to the design of a Multiple-Input-Multiple-Output (MIMO) flight control system (FCS) for a UH-60 Black Hawk Helicopter. In the first, a set of MISO systems, mathematically equivalent to the MIMO system, was determined. QFT was applied to each member of the set simultaneously. In the second, the same set of equivalent MISO systems were analyzed sequentially, with closed loop response information from each loop utilized in subsequent MISO designs. The results of each technique were compared, and the advantages of the second, termed Sequential Loop Closure, were clearly evident.

Gorder, Peter James↗
NASA NTRSDate not supplied

Machine Learning based Aircraft Performance Model Estimation for Trajectory Prediction

The accurate prediction of aircraft trajectory by ground-based decision support tools is a critical component of air traffic management in the US National Airspace System (NAS). Accurate predictions of where the aircraft will be in the future or when they will arrive at specific locations (e.g., fixes) is a key enabler for sequencing and efficient arrival management of flights. Traditional physics based aircraft trajectory prediction relies on a simplified point-mass total energy model whose parameters are referred to as Aircraft Performance Model (APM) parameters. Even though the performance coefficients and weight of an aircraft are a vital part of the aircraft performance model’s predictions and accuracy, these coefficients are proprietary in nature and therefore, unavailable to decision-support tools. Current approaches freeze some coefficients to default base of aircraft data (BADA) values and optimize others. However, the APM parameters are highly coupled by the flight dynamics and prioritizing one parameter over others leads to bias and skewed predictions. To alleviate this problem, we provide a combined optimization framework to predict all the critical (thrust, drag and weight) APM parameters. This paper is focused on training Machine Learning (ML) models that map historical flights to optimized APM parameters that provide the best fit (in terms of prediction error). Our dataset obtained from NASA’s Sherlock data warehouse is comprised of thousands of historical flights and includes weather and track data collected from 2019. Using different subsets of relevant features (e.g., aircraft type), we trained several ML models to estimate the aircraft’s take off weight, drag polar coefficients (both parasitic and lift induced), and thrust settings (multiplier applied to the maximum engine thrust). The chosen flights are from three of the most common aircraft types (B738, B737, and A320) arriving at four airports (LAX, DEN, MSP, and DFW). Our ML approach is comprised of two different solutions: 1- using a subset of features that are known prior to the flight departure and do not change during flight (such as engine type, current temperature at departure & destination airports, aircraft type) and 2 - using a subset of temporal features of the flight trajectory (such as cruise altitude, Mach, airspeed, and rate of climb) in addition to the pre-departure features from the first solution. The labels or target variables are the APM parameters that were obtained by an optimized ordinary differential equations (ODE) fitting process (applied to individual flights). The ODE-fitting is very time intensive and is therefore performed offline. Thus, training an ML model to learn the relationship between the flight features and ODE-generated labels enables faster estimation of the APM parameters and is therefore amenable to real-time prediction. Various ML models including linear regression, random forest, XGBoost, and neural network were trained, and the results are compared. After model validation and hyperparameter-tuning, we observed that the Random Forest model outperformed the other three models by the overall mean square error (MSE) of 2% for the first solution and 1.5% for the second solution. Finally, the ML-derived parameters are compared against default BADA APM parameters using NASA’s Autonomy Development toolkit (ADK) simulation software. The simulation results for one of each aircraft type is shown and discussed.

Aida Sharif Rohani↗
NASA NTRS1987

Control of aircraft landing approach in wind shear

Wind and wind shear components are estimated and used for controlling an externally-blown flap STOL aircraft and a B-727 during landing approach under the JAWS microburst profile. A combination of feedforward and feedback concepts is used. The objective is tracking of airspeed and glide slope. Both an asymptotic disturbance rejection scheme, which is equivalent to MIMO zero assignment, and a linear quadratic scheme prove to be successful. Higher angle-of-attack is used only after thrust saturation. Downdraft is found to be more difficult to counter for STOL aircraft than is horizontal wind shear. A third design formulation based on successive loop closure is also presented. A 'Wind Shear Penetration Index' is described, which offers a simple and quantitative evaluation of an aircraft's ability to safely penetrate a wind shear. This index is particularly useful if used with Doppler radars.

Chu, Peter Yaohwa↗
NASA NTRS1985

Optimal flight paths through microburst wind profiles

The problem of safe microburst wind shear encounter during the approach and climb-out flight phases is addressed using flight path optimization. The purpose was to investigate the physical limits of safe penetration and to determine control strategies that take full advantage of those limits. Optimal trajectories for both jet transport and general aviation aircraft were computed for encounters with idealized and actual microburst profiles. The results demonstrate that limits to control system design rather than to the aircraft's physical performance may be the deciding factor in an aircraft's capability for safe passage through a wide class of microbursts. The best control strategies responded to airspeed loss in an unconventional manner: by raising the nose to maintain lift.

Psiaki, M. L.↗
NASA NTRS2018

Output Measurement Equations for Flexible Aircraft Flight Dynamics

A summary of output measurement equations for onboard sensors used in flight testing of flexible aircraft is presented. These equations include the effects of structural flexibility and are considerably more complex than the standard equations for rigid-body aircraft. The output equations discussed include accelerations from linear accelerometers, strains, angular rates, angular accelerations, Euler angles, true airspeed, and air flow angles. The output equations are derived in full form and then simplified in some cases. Linearized output equations, suitable for state-space or transfer function models, are also developed. Example flight test data from the X-56A subscale aeroelastic demonstrator is discussed, for reference.

Grauer, Jared A.↗
NASA NTRS2019

Response Timing: Low Airspeed (Energy) Alerting

In response to NTSB Safety Recommendation A-14-043, the FAA was asked to task a panel of human factors, aviation operations, and aircraft design specialists, such as the Avionics Systems Harmonization Working Group (ASHWG), to develop design requirements for context-dependent low energy alerting systems for airplanes engaged in commercial operations. This recommendation is in association to the July 6, 2013, accident involving a Boeing 777-200ER, Korean registration HL7742, operating as Asiana Airlines flight 214, which was on approach to runway 28L when it struck a seawall at San Francisco International Airport (SFO), San Francisco, California. The FAA asked for human factor support from NASA in developing design requirements for context-dependent low energy alerting systems for airplanes engaged in commercial operations. Recently the ASHWG chair asked for continued support in examining flightcrew alert response timing and requested that NASA update the previous working paper on this subject. This product/paper will be provided to the ASHWG as part of the ongoing assignments from each of the ASHWG members in support of developing requirements and guidance for context-dependent low energy alerting systems for airplanes. The ASHWG is made up of interested parties from government and industry.

response timing↗
NASA NTRS2017

Stall Recovery Guidance Using Fast Model Predictive Control

Based on a detailed analysis of recent loss-of-control events, the Aircraft State Awareness Joint Safety Analysis Team has identified the need to develop algorithms and display strategies to provide control guidance for recovery from approach-to-stall or stall. In order to be effective, such guidance should enhance the pilots ability to execute the Federal Aviation Administrations recommended stall recovery procedure. This paper explores the use of a fast model predictive control algorithm that determines near optimal recovery guidance, which quantifies the aircraft configuration and situation dependent recovery information required to maximize the effectiveness of the recovery. This information includes the magnitude of the initial pitch down maneuver, the specific amount of airspeed and thrust needed before pulling out of the recovery dive, as well as the maximum pitch-up rate that can be sustained without causing a secondary stall. The algorithm was integrated and tested with an in-house desktop simulator that implements the General Transport Aircraft model and the associated stall aircraft dynamics. Preliminary results are presented to demonstrate the use of the proposed approach as a recovery aid for pilots.

predictive control↗
NASA NTRS1983

Time controlled descent guidance algorithm for simulation of advanced ATC systems

Concepts and computer algorithms for generating time controlled four dimensional descent trajectories are described. The algorithms were implemented in the air traffic control simulator and used by experienced controllers in studies of advanced air traffic flow management procedures. A time controlled descent trajectory comprises a vector function of time, including position, altitude, and heading, that starts at the initial position of the aircraft and ends at touchdown. The trajectory provides a four dimensional reference path which will cause an aircraft tracking it to touchdown at a predetermined time with a minimum of fuel consumption. The problem of constructing such trajectories is divided into three subproblems involving synthesis of horizontal, vertical, and speed profiles. The horizontal profile is constructed as a sequence of turns and straight lines passing through a specified set of waypoints. The vertical profile consists of a sequence of level flight and constant descent angle segments defined by altitude waypoints. The speed profile is synthesized as a sequence of constant Mach number, constant indicated airspeed, and acceleration/deceleration legs. It is generated by integrating point mass differential equations of motion, which include the thrust and drag models of the aircraft.

Lee, H. Q.↗
NASA NTRS1976

Description of a landing site indicator (LASI) for light aircraft operation

An experimental cockpit mounted head-up type display system was developed and evaluated by LaRC pilots during the landing phase of light aircraft operations. The Landing Site Indicator (LASI) system display consists of angle of attack, angle of sideslip, and indicated airspeed images superimposed on the pilot's view through the windshield. The information is made visible to the pilot by means of a partially reflective viewing screen which is suspended directly in frot of the pilot's eyes. Synchro transmitters are operated by vanes, located at the left wing tip, which sense angle of attack and sideslip angle. Information is presented near the center of the display in the form of a moving index on a fixed grid. The airspeed is sensed by a pitot-static pressure transducer and is presented in numerical form at the top center of the display.

Fuller, H. V.↗
NASA NTRSDate not supplied

Classical Flutter Analysis of X-57 Aircraft Mod II, III, and IV Configurations

To support airworthiness assessment of the X-57 electric propulsion demonstrator aircraft, the National Aeronautics and Space Administration (NASA) completed classical flutter analysis of the Mod II, Mod III, and Mod IV aircraft configurations. Aeroelastic analysis was primarily performed using the ZAERO analysis code developed by Zona Technology. Supplemental computational fluid dynamics (CFD) flutter analysis for the Mod III and Mod IV configurations was performed using NASA’s FUN3D software to verify the aeroelastic behavior at deployed flaps conditions. The NASTRAN finite element models (FEMs) used for aeroelastic analysis were developed by NASA. The final Mod II FEM utilized shell elements for the wing and fuselage, and beam elements for the tail and wing control surfaces. For Mod III and Mod IV aircraft models, shell element wing FEMs developed throughout the Mod III/IV wing design cycle were utilized. The fuselage and empennage FEM components were shared between the Mod II, III, and IV aircraft models. ZAERO analyses predicted flutter boundaries were >60% beyond the X-57 flight-test envelope never exceed airspeed (V NE ) for all configurations. Aeroelastic Reynolds-averaged Navier–Stokes (RANS) CFD simulations using FUN3D of the Mod III/IV configurations predicted flap mode instability did not occur until at least speeds of 60% higher than the Mod III/IV maximum flap deployment airspeed (V FE ).

Keerti K. Bhamidipati↗
NASA NTRS2008

Preliminary Analysis of Acoustic Measurements from the NASA-Gulfstream Airframe Noise Flight Test

The NASA-Gulfstream joint Airframe Noise Flight Test program was conducted at the NASA Wallops Flight Facility during October, 2006. The primary objective of the AFN flight test was to acquire baseline airframe noise data on a regional jet class of transport in order to determine noise source strengths and distributions for model validation. To accomplish this task, two measuring systems were used: a ground-based microphone array and individual microphones. Acoustic data for a Gulfstream G550 aircraft were acquired over the course of ten days. Over twenty-four test conditions were flown. The test matrix was designed to provide an acoustic characterization of both the full aircraft and individual airframe components and included cruise to landing configurations. Noise sources were isolated by selectively deploying individual components (flaps, main landing gear, nose gear, spoilers, etc.) and altering the airspeed, glide path, and engine settings. The AFN flight test program confirmed that the airframe is a major contributor to the noise from regional jets during landing operations. Sound pressure levels from the individual microphones on the ground revealed the flap system to be the dominant airframe noise source for the G550 aircraft. The corresponding array beamform maps showed that most of the radiated sound from the flaps originates from the side edges. Using velocity to the sixth power and Strouhal scaling of the sound pressure spectra obtained at different speeds failed to collapse the data into a single spectrum. The best data collapse was obtained when the frequencies were left unscaled.

Khorrami, Mehdi R.↗
NASA NTRS2011

Flight Test Results of a GPS-Based Pitot-Static Calibration Method Using Output-Error Optimization for a Light Twin-Engine Airplane

As part of the NASA Aviation Safety Program (AvSP), a novel pitot-static calibration method was developed to allow rapid in-flight calibration for subscale aircraft while flying within confined test areas. This approach uses Global Positioning System (GPS) technology coupled with modern system identification methods that rapidly computes optimal pressure error models over a range of airspeed with defined confidence bounds. This method has been demonstrated in subscale flight tests and has shown small 2- error bounds with significant reduction in test time compared to other methods. The current research was motivated by the desire to further evaluate and develop this method for full-scale aircraft. A goal of this research was to develop an accurate calibration method that enables reductions in test equipment and flight time, thus reducing costs. The approach involved analysis of data acquisition requirements, development of efficient flight patterns, and analysis of pressure error models based on system identification methods. Flight tests were conducted at The University of Tennessee Space Institute (UTSI) utilizing an instrumented Piper Navajo research aircraft. In addition, the UTSI engineering flight simulator was used to investigate test maneuver requirements and handling qualities issues associated with this technique. This paper provides a summary of piloted simulation and flight test results that illustrates the performance and capabilities of the NASA calibration method. Discussion of maneuver requirements and data analysis methods is included as well as recommendations for piloting technique.

Martos, Borja↗
NASA NTRS2021

Go-Around Criteria Refinement for Transport Category Aircraft

Presently, airline pilots are trained to go around if, when lower than 500 ft above the ground, they are outside of a handful of parameters such as airspeed, position, and rate of descent. At times, pilots do not comply with these criteria, perhaps owing to their conservative nature or complexity. This paper examines potential refinements to the continue-to-land decision from the combined results of three flight simulator experiments. Potential refinements include simplifying the number of parameters and lowering the altitude at which pilots make the decision. First, refinements were developed by evaluating pilots’ touchdown performance and qualitative data in a variety of starting and environmental conditions. Second, 30 of those pilots evaluated the refinements under several induced instabilities during the approach. The results showed little difference in touchdown performance when lowering the decision altitude from 500 to 300 ft; however, significant differences arose when the decision altitude was lowered further to 100 ft. The proposed new criteria include assessments of deviations in airspeed and position, no rate-of-descent audio warning, and having an appropriate engine setting at 1000, 500, and 300 ft height above threshold. Additionally, a recommendation is made that if the proposed criteria are not met at the 1000 or 500 ft height above threshold the pilots may make corrections and continue the approach; however, if the criteria are not met at 300 ft, then a go-around should be performed.

stabilized approach criteria↗
NASA NTRS2013

Flight Test Results of an Angle of Attack and Angle of Sideslip Calibration Method Using Output-Error Optimization

As part of a joint partnership between the NASA Aviation Safety Program (AvSP) and the University of Tennessee Space Institute (UTSI), research on advanced air data calibration methods has been in progress. This research was initiated to expand a novel pitot-static calibration method that was developed to allow rapid in-flight calibration for the NASA Airborne Subscale Transport Aircraft Research (AirSTAR) facility. This approach uses Global Positioning System (GPS) technology coupled with modern system identification methods that rapidly computes optimal pressure error models over a range of airspeed with defined confidence bounds. Subscale flight tests demonstrated small 2-σ error bounds with significant reduction in test time compared to other methods. Recent UTSI full scale flight tests have shown airspeed calibrations with the same accuracy or better as the Federal Aviation Administration (FAA) accepted GPS 'four-leg' method in a smaller test area and in less time. The current research was motivated by the desire to extend this method for inflight calibration of angle of attack (AOA) and angle of sideslip (AOS) flow vanes. An instrumented Piper Saratoga research aircraft from the UTSI was used to collect the flight test data and evaluate flight test maneuvers. Results showed that the output-error approach produces good results for flow vane calibration. In addition, maneuvers for pitot-static and flow vane calibration can be integrated to enable simultaneous and efficient testing of each system.

Siu, Marie-Michele↗
NASA NTRS1986

Identification of linearized equations of motion for the fixed wing configuration of the rotor systems research aircraft

The purpose of this report is to establish linear, decoupled models of rigid body motion for the fixed wing configuration of the Rotor Systems Research Aircraft (RSRA). Longitudinal and lateral control surface fixed linear models were created from aircraft time histories using current system identification techniques. Models were obtained from computer simulation at 160 KCAS and 200 KCAS, and from flight data at 160 KCAS. Comparisons were performed to examine modeling accuracy, variation of dynamics with airspeed and correlation of simulation and flight data results. The results showed that the longitudinal and lateral linear models accurately predicted RSRA dynamics. The flight data results showed that no significant handling qualities problems were present in the RSRA fixed wing aircraft at the flight speed tested.

Balough, D. L.↗
NASA NTRS1974

Integrated propulsion/energy transfer control systems for lift-fan V/STOL aircraft

An integrated propulsion/control system for lift-fan transport aircraft is described. System behavior from full-scale experimental and piloted simulator investigations are reported. The lift-fan transport is a promising concept for short-to-medium haul civil transportation and for other missions. The lift-fan transport concept features high cruise airspeed, favorable ride qualities, small perceived noise footprints, high utilization, transportation system flexibility, and adaptability to VTOL, V/STOL, or STOL configurations. The lift-fan transport has high direct operating costs in comparison to conventional aircraft, primarily because of propulsion system and aircraft low-speed control system installation requirements. An integrated lift-fan propulsion system/aircraft low-speed control system that reduces total propulsion system and control system installation requirements is discussed.

Deckert, W. H.↗